Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Complexity Leadership in Learning Analytics: Drivers, Challenges, and Opportunities

    Tsai, Y-S., Poquet, O., Gašević, D., Dawson, S. & Pardo, A., 21 Oct 2019, In : British Journal of Educational Technology. 50, 6, p. 2839–2854

    Research output: Contribution to journalArticle

  2. SHEILA policy framework: Informing institutional strategies and policy processes of learning analytics

    Tsai, Y-S., Moreno-Marcos, P. M., Tammets, K., Kollom, K. & Gasevic, D., 9 Mar 2018, Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK'18). Sydney: ACM Press, 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. Empowering learners with personalised learning approaches? Agency, equity and transparency in the context of learning analytics

    Tsai, Y-S., Perrotta, C. & Gasevic, D., 2020, In : Assessment & Evaluation in Higher Education. 45, 4, p. 554-567 23 p.

    Research output: Contribution to journalArticle

  4. Blind source extraction of heart sound signals from lung sound recordings exploiting periodicity of the heart sound

    Tsalaile, T., Naqvi, S. M., Nazarpour, K., Sanei, S. & Chambers, J. A., 12 May 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. Institute of Electrical and Electronics Engineers (IEEE), p. 461-464 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: A comparison with the modified Irwin test

    Tse, K., Sillito, R., Keerie, A., Collier, R., Grant, C., Karp, N. A., Vickers, C., Chapman, K., Armstrong, J. D. & Redfern, W. S., 1 Apr 2018, In : Journal of Pharmacological and Toxicological Methods. 94, p. 1 - 13 13 p.

    Research output: Contribution to journalArticle

  6. State-dependent brainstem ensemble dynamics and their interactions with hippocampus across sleep states

    Tsunematsu, T., Patel, A., Onken, A. & Sakata, S., 14 Jan 2020, In : eLIFE. 9, 22 p., e52244.

    Research output: Contribution to journalArticle

  7. Probabilistic computation underlying sequence learning in a spiking attractor memory network

    Tully, P., Lindén, H., Hennig, M. H. & Lansner, A., 1 Jan 2013, In : BMC Neuroscience. 14, 2 p.

    Research output: Contribution to journalArticle

  8. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

    Tully, P. J., Lindén, H., Hennig, M. H. & Lansner, A., 23 May 2016, In : PLoS Computational Biology. 12, 5, 35 p., e1004954.

    Research output: Contribution to journalArticle

  9. Synaptic and nonsynaptic plasticity approximating probabilistic inference

    Tully, P. J., Hennig, M. H. & Lansner, A., 2014, In : Frontiers in synaptic neuroscience. 6, 8.

    Research output: Contribution to journalArticle

  10. BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget

    Turner, J., Crowley, E., O'Boyle, M., Storkey, A. & Gray, G., 30 Apr 2020, Proceedings to the International Conference on Learning Representations 2020. p. 1-15 15 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution